GUEST POST from Geoffrey Moore
Two topics that have been on my mind a lot lately are generative AI and trapped value, so I am delighted to have them come together in a single blog. Here’s how it plays out.
Releasing trapped value is the engine that fuels ROI from technology deployments. All systems trap value somewhere in their operations, something that is confirmed by the Second Law of Thermodynamics, which means there will never be a time when there is no ROI to be gained. Where it is to be gained from, on the other hand, is up for grabs. The goal of my advisory practice is to help clients target the most impactful sources of trapped value in their target markets and direct their product roadmaps and go-to-market initiatives accordingly.
When I consider the extraordinary potential of generative AI to release trapped value across virtually any set of systems, I think the industry is, at present, overly infatuated with co-piloting and overlooking a far more impactful source of trapped value staring them right in the face. Look, co-piloting is useful, but how much trapped value is there in the delta between unaided and aided performance from white-collar professionals? Some, for sure, but is this really the burning platform that will drive customer spending to a level that might justify the extraordinary valuations generative AI companies are garnering at present? Probably not. So, what could?
My choice would be the market-facing user interface to any and all systems of engagement. This is where enterprises seek to enlist their customers and partners to utilize their systems for purposes of marketing, sales, service, and commerce, and that is precisely what we, as their external constituencies, want to do. But, how well is this working? Well, compared to the twentieth century, when, effectively, we had no systems of engagement, amazingly well. But by twenty-first-century standards, truth be told, they suck.
Where is the trapped value? Two areas jump to mind. The first is passwords, which have gone from being a source of security to a source of breaches, all the while creating massive amounts of aggravation in the process. The second is the user interface itself. No matter how well designed it is, it is inherently unfamiliar to the first-time or even occasional end user. Because of this friction at the point of user interaction, I submit, systems of engagement are delivering far less than their full value-creating potential.
Enter generative AI. The conversational interface that ChatGPT taught us to know and love is familiar to anyone who speaks the same language as the vendor, and the video, sound, and image recognition capabilities, supplemented by information from the idiosyncratic features that every online device entails, are far better equipped to identify and authorize end users than any set of passwords of two-factor authentication. So, the friction-removing technology is already here. What we are lacking is the friction-removing killer app, the one that every enterprise would embrace in a heartbeat were it available to them.
That app is a universal user interface that can be bolted onto APIs from enterprise systems to mediate between the legacy instruction system of the underlying software and the desires and intentions of the occasional end user. This would entail a (Very) Small Language Model to be developed by enterprise application vendors, as well as a companion SLM from cybersecurity system vendors, but really, how hard is that, especially when compared to the ROI rewards?
This is not just a big opportunity. It is an urgent one as well. Governments and NGOs struggle today to finance systems of engagement that allow programs to scale in the social sector, and their adoption is far below what one would wish, in large part because of the layers of friction we continue to impose. Enterprises that are seeking to catch the next wave of disruption roiling their industries are desperate to engage the customer bases, but are falling short because it is just too painful.
It is hard for me to see a more compelling use case for generative AI at this time, and I hope that industry will agree and free us from the Lilliputian bonds that restrict us.
That’s what I think. What do you think?
— Image credit: Unsplash
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